Here’s how I would approach the issue: by asking how we know that a modeling approach is truly useful. The answer, I’d suggest, is that we look for surprising successful predictions. General relativity got its big boost when light did, in fact, bend as predicted. The theory of a natural rate of unemployment got a big boost when the Phillips curve turned into clockwise spirals, as predicted, during the stagflation of the 1970s.

So has there been anything like that in recent years? …Were there any interesting predictions from … models that were validated by events?

“Probably {scientists’} most deeply held values concern predictions: they should be accurate; quantitative predictions are preferable to qualitative ones; whatever the margin of permissible error, it should be consistently satisfied in a given field; and so on.”

“Confirmations should count only if they are the result of risky predictions; that is to say, if, unenlightened by the theory in question, we should have expected an event which was incompatible with the theory — an event which would have refuted the theory.”

Krugman, drawing on this tradition, points us to a solution for the deadlock in the ever-more-bitter public policy debate about our response to climate change: look for predictions, then test them.

The great oddity of the climate science debate

“Ad hominem attacks aren’t a final line of defense, they’re argument #1. …It’s about an attitude, the sense that righteousness excuses you from the need for hard thinking and that any questioning of the righteous is treason.” {Paul Krugman.}

Activists consider forecasts of models as like the Word of God. Skeptics mutter about vast conspiracies of climate scientists. Lost in this futile decades-long debate is discussion about the methodological testing necessary to create confidence that the results of climate models provide an adequate basis for public policy decisions that shape the world economy.

The necessary tools are well understood, and routinely applied in other fields. For example drugs are tested by prior review of study proposals, followed by analysis of their results by paid non-affiliated multi-disciplinary teams of experts (neither of which is done in climate science). Best of all are successful predictions, and successful risky predictions (for outcomes contrary to expectations) create strong confidence. These hard-won insights have had little influence on climate science. See these posts for examples…

So the bitter public policy debate rattles on, each side hoping for a brute-force political resolution that crushes the large fraction of the pubic that disagree with them. Perhaps that will happen, and perhaps that will produce a useful outcome. But we can do better.

Scientists could re-run older models with actual emissions, not projections, and comparing their forecasts with observed temperatures. These multi-decade predictions would provide objective, powerful data that might resolve the policy debate — or create a clear majority of public opinion to one side.

This will not happen without public pressure. As we see in Campaign 2016, our ruling elites prefer to give us a circus — treating us like children to be entertained rather than citizens to be informed. But we can stand up and re-take the reins of America, re-shaping the debates about climate change and other key issues.

31 thoughts on “Paul Krugman explains how to break the climate policy deadlock”

Of course the scientific principles espoused here are valid. The particular problem with climate change validation through observation is that it’s so damn slow and overlain by so many random variables that convincing validations take many decades. The main difference between the protagonists in this ‘debate’ is that physical scientists EXPECT that extra carbon dioxide will affect climate to some degree because of its spectral properties. So they are predisposed to accepting the climate models in question, they start from a different perspective. I think it’s as simple as that. But until those decades pass by their opponents will continue to be skeptical, (and of course they may just be right). The real problem is how best to handle these uncertainties, especially in the face of inevitable exaggerations from all directions. There are exaggerations of the consequences of climate change and of the prospects of technological solution or adaptation. Responses, or lack of responses, to such exaggerations are expensive and probably wasteful. That’s where politics and economics come in.

That’s a common excuse. It is unfounded. Climate model forecasts were made in each of the IPCC’s Assessment Reports. These give us 3 generations of multi-decade predictions that can be compared with actual results.

yes Brian Cox was on Australian TV last night with this argument is that all we have is the models because it is the future. I have heard him use that argument before. The problem I have is this argument is open ended as the paradigm can never be falsified as it always its in the future. Something that cannot be falsified cannot be rejected and so is counterproductive to the scientific advancement of knowledge – therefor it is not science or useful.

“with this argument is that all we have is the models because it is the future.”

I don’t know what that means, but it is certainly unrelated to what I propose — which is a testing of the models used in the past IPCC AR’s vs. data from after their publication (reducing the concern about tuning). These would give multi-decade predictions whose accuracy would tell us much, one way or another.

Some skeptics do just that. Just as some true believers claim that the skeptics are aided and abetted by the fossil-fuel industry.

On balance, the conspiracy fringe on both sides probably balance, except for what seems to me the academic and political conspiracy theorists.

The skeptics who are conspiracy theorists seem to me to lack scientific knowledge and skills as well as general education, probably accounting for a third of skeptics. Among the true believers the percentage lacking education both scientific and otherwise probably also account for a third.

However, among true believers there is another group, possibly a third or more who are educated in science and other disciplines but who have adopted two political strategies to deal with skeptics: ad hominem attacks and conspiracy theories. Merchants of Doubt is an example of a polemical work that exemplifies academic support for a conspiracy theory by true believers. Environmental activist groups have recently joined with state prosecutors to pursue a conspiracy theory involving Exxon and conservative think tanks.

It therefore appears that conspiracy theories account for a minority of skeptics and a majority of true believers.

So what do the majority of skeptics believe?

In my opinion, the majority would agree with Thomas Kuhn’s analysis on the role of leading scientists, mostly academics, as having an institutionalized role in maintaining prevailing paradigms in science, “normal science”. The majority of skeptics would accept “confirmation bias” as reinforcing the prevailing global warming paradigm. The majority would accept that social rewards lead people to accept the authority of leaders in most fields, including science.

The closest most educated skeptics get to conspiracy theory seems to be similar to the concerns expressed by President Eisenhower in his famous speech a little after he mentioned the military-industrial complex. Eisenhower expressed concern that the increase in Federal funding of academic science would have adverse effects on science itself.

“The prospect of domination of the nation’s scholars by Federal employment, project allocations, and the power of money is ever present and is gravely to be regarded. Yet, in holding scientific research and discovery in respect, as we should, we must also be alert to the equal and opposite danger that public policy could itself become the captive of a scientific technological elite.”

See also: Kuhn, Popper and Logical Positivism in Steve Fuller’s, The Knowledge Book, page 88. Google Books preview. Not all philosophers take such a critical view of Kuhn. Fuller and others regard Kuhn’s work as prescriptive, whereas others regard Kuhn’s work as descriptive.

As for climatology and climatologists, we should read the IPCC technical reports on climate science. Unfortunately, the key section does not appear until page 121 in the Technical Summary and page 126 in the main report:

Quote
The processes affecting climate can exhibit considerable natural variability. Even in the absence of external forcing, periodic and chaotic variations on a vast range of spatial and temporal scales are observed. Much of this variability can be represented by simple (e.g., unimodal or power law) distributions, but many components of the climate system also exhibit multiple states—for instance, the glacial-interglacial cycles and certain modes of internal variability such as El Niño-Southern Oscillation (ENSO) (see Box 2.5 for details on patterns and indices of climate variability). Movement between states can occur as a result of natural variability, or in response to external forcing. The relationship between variability, forcing and response reveals the complexity of the dynamics of the climate system: the relationship between forcing and response for some parts of the system seems reasonably linear; in other cases this relationship is much more complex, characterised by hysteresis (the dependence on past states) and a non-additive combination of feedbacks.
End of quote: Fifth Assessment Report of the Intergovernmental Panel on Climate Change, WGI, 2013

This statement is not quite as strong as earlier statements:
Quote:
14.2.2 Predictability in a Chaotic System The climate system is particularly challenging since it is known that components in the system are inherently chaotic; there are feedbacks that could potentially switch sign, and there are central processes that affect the system in a complicated, non-linear manner. These complex, chaotic, non-linear dynamics are an inherent aspect of the climate system. As the IPCC WGI Second Assessment Report (IPCC, 1996) (hereafter SAR) has previously noted, ?future unexpected, large and rapid climate system changes (as have occurred in the past) are, by their nature, difficult to predict. This implies that future climate changes may also involve ‘surprises?. In particular, these arise from the non-linear, chaotic nature of the climate system …
End of quote: WGI, Third Assessment Report, IPCC, 2001.

A physical scientist would prefer to read this near the beginning of the IPCC’s reports because the key scientific question is whether or not the climate system can be reliably predicted. How much confidence can be placed in the conclusions and predictions actually made by the IPCC both in the main report and the Summary for Policymakers?

This is important for economists, politicians, businesses and bureaucrats.

The IPCC says here that the climate system does behave deterministically and linearly over narrow ranges, but that climatologists know that the Earth’s climate is both non-linear and chaotic.

So what sort of mindset do scientists have who prepare the reports. Stephen Schneider is one who has been misquoted by omission of the last part of his personal reflections, the whole of whhich is cited here:

original quote:

“On the one hand, as scientists we are ethically bound to the scientific method, in effect promising to tell the truth, the whole truth, and nothing but – which means that we must include all doubts, the caveats, the ifs, ands and buts. On the other hand, we are not just scientists but human beings as well. And like most people we’d like to see the world a better place, which in this context translates into our working to reduce the risk of potentially disastrous climate change. To do that we need to get some broad based support, to capture the public’s imagination. That, of course, means getting loads of media coverage. So we have to offer up scary scenarios, make simplified, dramatic statements, and make little mention of any doubts we might have. This “double ethical bind” we frequently find ourselves in cannot be solved by any formula. Each of us has to decide what the right balance is between being effective and being honest. I hope that means being both.”

Not only skeptics should be offended by this statement but everyone, physical scientists, social scientists, politicians and the general public.

The world does not need physical scientists to “… to offer up scary scenarios, make simplified, dramatic statements, and make little mention of any doubts…” That is the job of political activists and professional politicians.

What I see is bad science, by scientists who admit that the climate system is non-linear and chaotic, but persist in treating it as deterministic and linear and then finding patterns in chaos that confirms their biases. A close reading of the mostly qualitative conclusions in both WGI and the Summary for Policymakers seems to me to be based on subjective judgments.

As a result, I am not in a position to say where the authors found their balance in the broad spectrum “…between being effective and being honest…”. To my mind, the “double ethical bind” is between accepting the responsibility for the science wherever it leads, while at the same time avoiding self-deception. As Richard Feynman put it, “…the first principle is that you must not fool yourself, and you are the easiest person to fool.”http://www.ar-tiste.com/feynman-on-honesty.html

“It therefore appears that conspiracy theories account for a minority of skeptics”

In the absence of reliable surveys — and a consensus as to the meaning of “skeptic” — we can only guess. If we look at the people who write and comment at the major climate skeptic websites, imo a majority believe that there is a conspiracy to distort the climate temperature record. It is one of their core beliefs.

I did numerical modeling in physical chemistry, and your suggestions are good, but NOT new. The typical “scientist” knows all of this. If they aren’t already doing this, they are either stupid, lazy or purposely misleading. I put “scientist” in quotes because if one doesn’t already do these things one is not a person worthy of the label.

Sorry to be so bunt, but that’s how a lot of us professional scientists see this issue.

My posts discussing this proposal in detail document other similar proposals.

“The typical “scientist” knows all of this.”

Which is why I said “This will not happen without public pressure.”

“If they aren’t already doing this, they are either stupid, lazy or purposely misleading.”

The history of science says otherwise, showing that methodological reforms are often fiercely opposed by scientists. Human nature. People like processes that give them the greatest freedom to do what they want, and resists review and supervision. Similar reforms to the drug discovery process were imposed by government legislation and enforced by the FDA.

I agree with wkevinw that the validation exercises are now absolutely required and should be publicized better. Using data up to, e.g., 1990, what did a model estimated on data available up to that point forecast for the period up to the present? And why did all the models in the 1970s that predicted cooling fail? I’ve never seen these validations in fairly intense reading on the subject.

Professor Zharkova seems to indicate that these projections are not being blended into the exogenous variable assumptions used in climate modeling, at least in some scenarios, which is clearly dishonest. If this is the level of intellectual integrity on the climate change side (which is despised not so much for its projections as for the fascistic big government solutions that are being proposed, that would raise huge amounts of tax revenue and give the proceeds to bureaucrats to administer…), then the climate modelers lose any shred of credibility with me.

We may see cooling the near future, leading to absolutely no action being taken, followed by a whiplash when solar cycle 26 presumably heats the planet up. But hey, megafauna extinctions are humankind’s speciality, perhaps including ourselves.

“Using data up to, e.g., 1990, what did a model estimated on data available up to that point forecast for the period up to the present? And why did all the models in the 1970s”

Those models were toys running on toys compared to global climate models using in the IPCC’s Assessment Reports. The computer in a Apple Watch is more powerful than a Cray-2 supercomputer (released 1985), and has less than one-ten thousandth of the power of current supercomputers. See these graphics to see the evolution of computer hardware.

The models using in the first AR (1990) are primitive, but of some relevance. Those in the second AR (1995) are comparable and relevant.

Let’s not imitate the alarmists and start believing as gospel the work of scientists that has not been replicated by others. Science advances by breakthroughs — often made on the fringes of science (i.e., working far from the consensus). However, most work on the fringes is not successfully replicated and fades away.

Hey Fabio, dude, one of the references (Hathaway) is NASA saying solar cycle 25 will be exceptionally weak! That makes two citations! Who says their results can’t be replicated? And why not? Presumably Hathaway and Zharkova published their methods and data, and the mainstream dispute will be over statistical methods–the easiest way to suppress non-mainstream findings from top journals. References?

In any event, you have resorted to name-calling (“fringe”) and I have correspondingly lost respect for your analysis. A categorical debunking of “fringe” (i.e., anomalous) findings is exactly the opposite of a proper scientific attitude.

This is the way mainstream economics and climate science deal with anomalies, by calling them conspiracy theories, or “fringe.” Comments like these are why I stopped reading your blog much.

This post was about creating confidence in the modeling and how that has not happened. And in the wordy, pithy comments here we get almost nowhere.
So.
I’ll go read Ezra Klein and how we will soon suppress basic male sexuality all over the Place.
And the summer sun is still shining.

Fab – if you can find a reference that details the solar output assumptions typically used for climate modeling, or one that specifically repudiates the solar cycle 25 forecast methodology, I would be interested. Temperature is heavily dependent on solar output. Your side would benefit from knowing that any imminent cooling is temporary and does not invalidate the general forecast, wouldn’t it?

To repeat myself, the relevant question is not the forecast of solar activity — but its impact on Earth’s climate.

(2) “Temperature is heavily dependent on solar output.”

That’s a question on the frontier of current climate science, being fought out in the literature. The current consensus is, so far as I can tell, that the tiny variations of solar output have little effect on Earth’s climate.

(3) “Your side would benefit from knowing that any imminent cooling is temporary and does not invalidate the general forecast, wouldn’t it? ”

Too dumb for reply. You’re just making stuff up and attributing it to me.

(4) “I have enjoyed fencing with you a few times.”

You are fencing with yourself, and pretending it is me. I do not enjoy your grossly false assertions about my statements. Your failure to reply in any meaningful fashion to debunking of your false statements suggests that I’m wasting my time with you.

Okay, Fab, so the Dalton and Maunder Minima were not caused by reductions in solar output? And Milankovitch cycles, the premier ice age theory, are also false? How original! Those are pretty mainstream conclusions as far as I can tell. For example, from PNAS: “Geophysical, archaeological, and historical evidence support a solar-output model for climate change”, Charles A. Perry et al, PNAS. Abstract:

Although the processes of climate change are not completely understood, an important causal candidate is variation in total solar output. Reported cycles in various climate-proxy data show a tendency to emulate a fundamental harmonic sequence of a basic solar-cycle length (11 years) multiplied by 2N (where N equals a positive or negative integer). A simple additive model for total solar-output variations was developed by superimposing a progression of fundamental harmonic cycles with slightly increasing amplitudes. The timeline of the model was calibrated to the Pleistocene/Holocene boundary at 9,000 years before present. The calibrated model was compared with geophysical, archaeological, and historical evidence of warm or cold climates during the Holocene. The evidence of periods of several centuries of cooler climates worldwide called “little ice ages,” similar to the period anno Domini (A.D.) 1280–1860 and reoccurring approximately every 1,300 years, corresponds well with fluctuations in modeled solar output. A more detailed examination of the climate sensitive history of the last 1,000 years further supports the model. Extrapolation of the model into the future suggests a gradual cooling during the next few centuries with intermittent minor warmups and a return to near little-ice-age conditions within the next 500 years. This cool period then may be followed approximately 1,500 years from now by a return to altithermal conditions similar to the previous Holocene Maximum.

or this: “Variability of the solar cycle length during the past five centuries and the apparent association with terrestrial climate”, K. Lassen and E. Friis-Christensen, Journal of Atmospheric and Terrestrial Physics, July 1995. Abstract:

Solar data have been used as parameters in a great number of studies concerning variations of the physical conditions in the Earth’s upper atmosphere. The varying solar activity is distinctly represented by the 11-yr cycle in the number of sunspots. The length of this sunspot period is not fixed. Actually, it varies with a period of 80–90 yr. Recently, this variation has been found to be strongly correlated with long-term variations in the global temperature. Information about northern hemisphere temperature based on proxy data is available back to the second half of the sixteenth century. Systematic monitoring of solar data did not take place prior to 1750. Therefore, a critical assessment of existing and proxy solar data prior to 1750 is reported and tables of epochs of sunspot minima as well as sunspot cycle lengths covering the interval 1500–1990 are presented. The tabulated cycle lengths are compared with reconstructed and instrumental temperature series through four centuries. The correlation between solar activity and northern hemisphere land surface temperature is confirmed.

And even the biggest naysayer doesn’t deny a possible connection between solar output and terrestrial climate, but only makes some inconclusive remarks about data handling: “Solar activity and terrestrial climate: an analysis of some purported correlations” by Peter Laut in Journal of Atmospheric and Solar-Terrestrial Physics, May 2003. Abstract:

The last decade has seen a revival of various hypotheses claiming a strong correlation between solar activity and a number of terrestrial climate parameters: Links between cosmic rays and cloud cover, first total cloud cover and then only low clouds, and between solar cycle lengths and Northern Hemisphere land temperatures. These hypotheses play an important role in the scientific as well as in the public debate about the possibility or reality of a man-made global climate change. I have analyzed a number of published graphs which have played a major role in these debates and which have been claimed to support solar hypotheses. My analyses show that the apparent strong correlations displayed on these graphs have been obtained by an incorrect handling of the physical data. Since the graphs are still widely referred to in the literature and their misleading character has not yet been generally recognized, I have found it appropriate to deliver the present overview. Especially, I want to caution against drawing any conclusions based upon these graphs concerning the possible wisdom or futility of reducing the emissions of man-made greenhouse gases.

My findings do not by any means rule out the existence of important links between solar activity and terrestrial climate. Such links have over the years been demonstrated by many authors. The sole objective of the present analysis is to draw attention to the fact that some of the widely publicized, apparent correlations do not properly reflect the underlying physical data.

(1) I said: “That’s a question on the frontier of current climate science, being fought out in the literature.” You reply with some examples from the literature — implying that this is a rebuttal, when in fact it is a confirmation of what I said.

(2) “You are exceedingly grumpy”

Lies about what I’ve said do that.

(3) “I won’t be back soon.”

That’s probably for the best. Your defective reading skills show you are getting little from the material here. Certainly the lies in your comments won’t be missed.

(1) “so the Dalton and Maunder Minima were not caused by reductions in solar output?”

I said nothing remotely like that. I said that this issue is “on the frontier of current climate science, being fought out in the literature.”

(2) “And Milankovitch cycles, the premier ice age theory, are also false?”

Multiple lies in one sentence! First, I didn’t say anything remotely like that (your statements are becoming delusional). Second, the M cycles are not caused by variations in the Sun’s output, but by “Variations in the Earth’s eccentricity, axial tilt, and precession”. See this explanation.

(3) “so the Dalton and Maunder Minima were not caused by reductions in solar output?”

Those are minima in the number of sunspots. Yes, they are associated with a reduction in solar output — but not necessarily caused by it (I don’t know what the current theory is about their relationship).

But we’re discussing Earth’s climate. The relationship of sunspots to solar activity is not relevant. Even more bizarre is that you believe I’ve said anything about this.

to the editor
‘Those are minima in the number of sunspots. Yes, they are associated with a reduction in solar output — but not necessarily caused by it (I don’t know what the current theory is about their relationship).’

One idea used to link the correlation of weak sunspot cycles with the the climate minimums involves cosmic rays. When the sun is quiet the solar wind is weaker, the upper atmosphere is less excited and shrinks. The solar wind normally blows aways cosmic rays but when it its week more cosmic rays can enter the atmosphere and seed low level clouds, especially at high latitudes. Low level clouds cool the surface (or more correctly doesn’t allow the sun to warm it up during the day). I had experience of this in Tasmania. Some cold days in winter were forecast to reach a max of about 12 C – one the rare days when the cloud would not lift (as expected by forecasters) the temp struggled to get into double figures (very cold by Australian standards). Quiet sun more days when the clouds don’t lift.

“One idea used to link the correlation of weak sunspot cycles with the the climate minimums involves cosmic rays.”

Yes, that is the current theory (still unproven & controversial). But that’s not what spike said. He said “so the Dalton and Maunder Minima were not caused by reductions in solar output?” — referring not to the relationship of solar output to Earth’s climate, but a causal relationship of solar output to the number of sunspots.

Also note that the new revised sunspot historical count (produced by Lief Svalgaard et al) upsets the simple chronology so often used.

For a interesting discussion about the data (weak data) supporting the theory that variations in solar activity have affected Earth’s climate during the past few million years — see astrophystist Lief Svagaard’s comments here. Esp see his graphs here and here, showing that in fact there is only a weak correlation between Earth’s climate and sunspot activity (i.e., the claims of a strong patter are false).

I suggest ignoring the post and most comments. Just search for “lsvagaard”, which will scroll you thru his comments.

Thanks for posting the link to the video of this interesting presentation. It went into the spam filter, hence the delay in getting it up.

This is a great intro to the predictions in climate science, a mixed bag of hits and misses. The meat is after 57 minutes. He makes some realistic comments (“it would be nice to have predicted this, but we didn’t”). He concludes with the assertion that “the standard model has done pretty well, our predictions have done pretty well”. Doesn’t give any evidence as to reliability of models’ predictions — or cite any p-r literature. Just hand-waving.

He then goes off far beyond anything in the IPCC, into fringe doomster land. Closing begins with “Will this be the epitaph for human civilization.” Followed more more nonsense.